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Update README
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‎OnnxStack.StableDiffusion/README.md‎

Lines changed: 84 additions & 55 deletions
Original file line numberDiff line numberDiff line change
@@ -86,44 +86,76 @@ internal class AppService : IHostedService
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while (true)
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{
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System.Console.WriteLine("Please type a prompt and press ENTER");
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var prompt = System.Console.ReadLine();
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System.Console.WriteLine("Please type a prompt and press ENTER");
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var prompt = System.Console.ReadLine();
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System.Console.WriteLine("Please type a negative prompt and press ENTER (optional)");
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var negativePrompt = System.Console.ReadLine();
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System.Console.WriteLine("Please type a negative prompt and press ENTER (optional)");
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var negativePrompt = System.Console.ReadLine();
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System.Console.WriteLine("Please enter image filepath for Img2Img and press ENTER (optional)");
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var inputImageFile = System.Console.ReadLine();
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var promptOptions = new PromptOptions
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{
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Prompt = prompt,
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NegativePrompt = negativePrompt,
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SchedulerType = SchedulerType.LMSScheduler,
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InputImage = new InputImage
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{
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ImagePath = inputImageFile
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}
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};
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var schedulerOptions = new SchedulerOptions
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// Example only, full config depends on model
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// appsettings.json is recommended for ease of use
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var modelOptions = new ModelOptions
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{
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Name = "Stable Diffusion 1.5",
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ExecutionProvider = ExecutionProvider.DirectML,
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ModelConfigurations = new List<OnnxModelSessionConfig>
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{
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Seed = Random.Shared.Next(),
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GuidanceScale = 7.5f,
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InferenceSteps = 30,
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Height = 512,
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Width = 512,
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Strength = 0.6f // Img2Img
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};
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System.Console.WriteLine("Generating Image...");
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var outputFilename = Path.Combine(_outputDirectory, $"{schedulerOptions.Seed}_{promptOptions.SchedulerType}.png");
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var result = await _stableDiffusionService.GenerateAsImageAsync(prompt, options);
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if (result is not null)
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{
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await result.SaveAsPngAsync(outputFilename);
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System.Console.WriteLine($"Image Created, FilePath: {outputFilename}");
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new OnnxModelSessionConfig
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{
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Type = OnnxModelType.Unet,
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OnnxModelPath = "model path"
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}
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}
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};
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var promptOptions = new PromptOptions
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{
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Prompt = prompt,
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NegativePrompt = negativePrompt,
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DiffuserType = DiffuserType.TextToImage,
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// Input for ImageToImage
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// InputImage = new InputImage(File.ReadAllBytesAsync("image to image filename"))
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};
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var schedulerOptions = new SchedulerOptions
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{
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Seed = Random.Shared.Next(),
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GuidanceScale = 7.5f,
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InferenceSteps = 30,
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Height = 512,
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Width = 512,
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SchedulerType = SchedulerType.LMS,
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};
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// Generate Image Example
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var outputFilename = Path.Combine(_outputDirectory, $"{schedulerOptions.Seed}_{schedulerOptions.SchedulerType}.png");
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var result = await _stableDiffusionService.GenerateAsImageAsync(modelOptions, promptOptions, schedulerOptions);
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if (result is not null)
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{
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// Save image to disk
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await result.SaveAsPngAsync(outputFilename);
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}
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// Generate Batch Example
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var batchOptions = new BatchOptions
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{
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BatchType = BatchOptionType.Seed,
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ValueTo = 20
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};
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await foreach (var batchResult in _stableDiffusionService.GenerateBatchAsImageAsync(modelOptions, promptOptions, schedulerOptions, batchOptions))
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{
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// Save image to disk
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await batchResult.SaveAsPngAsync(outputFilename);
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}
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}
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}
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@@ -151,48 +183,45 @@ Each model can be assigned to its own device, which is handy if you have only a
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"OnnxStackConfig": {
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"Name": "StableDiffusion 1.5",
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"IsEnabled": true,
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"PadTokenId": 49407,
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"BlankTokenId": 49407,
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"TokenizerLimit": 77,
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"EmbeddingsLength": 768,
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"ScaleFactor": 0.18215,
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"ModelConfigurations": [{
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"Type": "Unet",
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"DeviceId": 0,
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"ExecutionProvider": "DirectML",
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"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\unet\\model.onnx"
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},
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"PipelineType": "StableDiffusion",
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"Diffusers": [
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"TextToImage",
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"ImageToImage",
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"ImageInpaintLegacy"
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],
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"DeviceId": 0,
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"InterOpNumThreads": 0,
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"IntraOpNumThreads": 0,
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"ExecutionMode": "ORT_SEQUENTIAL",
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"ExecutionProvider": "DirectML",
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"ModelConfigurations": [
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{
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"Type": "Tokenizer",
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"DeviceId": 0,
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"ExecutionProvider": "Cpu",
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"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\cliptokenizer.onnx"
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},
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{
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"Type": "Unet",
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"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\unet\\model.onnx"
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},
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{
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"Type": "TextEncoder",
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"DeviceId": 0,
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"ExecutionProvider": "Cpu",
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"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\text_encoder\\model.onnx"
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},
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{
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"Type": "VaeEncoder",
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"DeviceId": 0,
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"ExecutionProvider": "Cpu",
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"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\vae_encoder\\model.onnx"
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},
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{
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"Type": "VaeDecoder",
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"DeviceId": 0,
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"ExecutionProvider": "Cpu",
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"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\vae_decoder\\model.onnx"
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},
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{
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"Type": "SafetyChecker",
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"IsDisabled": true,
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"DeviceId": 0,
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"ExecutionProvider": "Cpu",
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"OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\safety_checker\\model.onnx"
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}]
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}
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]
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}
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}
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```

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